SocialSens 2018 Is co-located with IoTDI 2018!


Social sensing has emerged as a new paradigm for collecting sensory measurements by means of "crowd-sourcing" sensory data collection tasks to a human population. Humans can act as sensor carriers (e.g., carrying GPS devices that share location data), sensor operators (e.g., taking pictures with smart phones), or as sensors themselves (e.g., sharing their observations on Twitter). The proliferation of sensors in the possession of the average individual, together with the popularity of social networks that allow massive information dissemination, heralds an era of social sensing that brings about new research challenges and opportunities in this emerging field.

The third international workshop on social sensing will bring together researchers and engineers from academia, industry, and government to present recent advances in both theoretical and experimental research. The scope of the workshop includes social sensing, ubiquitous, mobile and pervasive sensing, participatory and opportunistic sensing, urban sensing, social signal processing, information and coding theory, information processing and knowledge discovery from sensor data, data reliability, privacy and security issues, cyber-physical-systems with human-in-the-loop. We invite technical papers describing original ideas, exciting results, and/or real-world experiences involving the social sensing paradigm.



Keynote speaker: Prof. Radu Marculescu (Carnegie Mellon University)
Title: Understanding and Engineering Social Signals: A Network- and Data-Driven Perspective
Abstract: How do we communicate using Twitter? What are the hidden patterns of interaction behind our everyday communication? How exactly our ideas propagate in space and time? Can we understand and engineer the way in which various properties of social media evolve over time? Finally, how about addressing similar questions at micro- or planetary-scale as relevant to biological or climate systems? In this talk, I plan to address such questions and offer some surprising insights that came about by bringing machine learning and network science together in such complex settings. In other words, this talk is about the subtle interplay between science and engineering as seen through a computational lens.
Bio: Radu Marculescu is the Kavčić-Moura Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University, USA. He received his Ph.D. in Electrical Engineering from the University of Southern California in 1998. Marculescu has received several best paper awards in the area of design automation and embedded systems design. He has been involved in organizing several international symposia, conferences, workshops, as well as being guest editor of special issues in archival journals and magazines. His research focuses on modelling and optimization of embedded systems, cyber-physical systems, and biological systems. Nowadays, he is particularly interested in data and network science approaches that can bring science, engineering, and humanities closer together. Radu Marculescu is a fellow of IEEE.

Organizing Committee

General Chair
  • Tim Hanratty, US Army Research Lab, USA

Program Chairs
  • Jana Diesner, University of Illinois at Urbana-Champaign, USA
  • Lu Su, State University of New York at Buffalo, USA

Steering Committee
  • Tarek Abdelzaher, University of Illinois at Urbana-Champaign, USA
  • Charu Aggarwal, IBM Research, USA
  • Jiawei Han, University of Illinois at Urbana Champaign, USA
  • Edward Palazzolo, U.S. Army Research Office, USA
  • Mani Srivastava, UCLA, USA
  • Bolek Szymanski, Rensselaer Polytechnic Institute, USA
  • Dong Wang, University of Notre Dame, USA